For details about data description see here
load(file = "../output/mediatenor.Rda")df.reduced %>%
filter(category == "daily_print") %>%
ggplot(aes(year, count, color=medium)) +
geom_line() +
facet_wrap(~p_group) +
labs(x="", y="", color="",
title="Tageszeitungen: Anzahl d. Beobachtungen")p <- df.reduced %>%
filter(category == "daily_print")
ggplot(p, aes(year, wertung, color=p_group,
group=p_group)) +
geom_point(size=p$count/10000) + geom_line() +
facet_wrap(~medium, ncol = 3) +
geom_hline(yintercept = 0, color="grey10",
size=0.3, linetype = 2) +
labs(x="", y="",
title="Tageszeitungen: Wertung (ungewichtet)",
subtitle = "Pointsize: Obs/10.000",
color="") +
theme(axis.text.x = element_text(angle = 90)) +
scale_x_continuous(breaks = seq(min(df.reduced$year),max(df.reduced$year),2)) ## Warning: Removed 31 rows containing missing values (geom_point).
## Warning: Removed 1 rows containing missing values (geom_path).
df.reduced %>%
filter(category == "magazine_print") %>%
ggplot(aes(year, count, color=medium)) +
geom_line() +
facet_wrap(~p_group) +
labs(x="", y="", color="",
title="Magazine und Wochenzeitungen: Anzahl d. Beobachtungen")p <- df.reduced %>%
filter(category == "magazine_print")
ggplot(p, aes(year, wertung, color=p_group, group = p_group)) +
geom_point(size=p$count/10000) + geom_line() +
facet_wrap(~medium, ncol = 5) +
geom_hline(yintercept = 0, color="grey10",
size=0.3, linetype = 2) +
labs(x="", y="", color="",
title="Magazine und Wochenzeitungen: Wertung (ungewichtet)",
subtitle = "Pointsize: Obs/10.000") +
theme(axis.text.x = element_text(angle = 90)) +
scale_x_continuous(breaks = seq(min(df.reduced$year),max(df.reduced$year),2)) ## Warning: Removed 13 rows containing missing values (geom_point).
df.reduced %>%
filter(category == "news_tv") %>%
ggplot(aes(year, count, color=medium)) +
geom_line() +
facet_wrap(~p_group) +
labs(x="", y="", color="",
title="Nachrichtensendungen: Anzahl d. Beobachtungen")p <- df.reduced %>%
filter(category == "news_tv")
ggplot(p, aes(year, wertung, color=p_group)) +
geom_point(size=p$count/10000) + geom_line() +
facet_wrap(~medium, ncol = 3) +
geom_hline(yintercept = 0, color="grey10",
size=0.3, linetype = 2) +
labs(x="", y="",
title="Nachrichtensendungen (ungewichtet)",
subtitle = "Pointsize: Obs/10.000",
color="") +
theme(axis.text.x = element_text(angle = 90)) +
scale_x_continuous(breaks = seq(min(df.reduced$year),max(df.reduced$year),2)) ## Warning: Removed 4 rows containing missing values (geom_point).
df.reduced %>%
filter(category == "polit_tv") %>%
ggplot(aes(year, count, color=medium)) +
geom_line() +
facet_wrap(~p_group) +
labs(x="", y="", color="",
title="Politische TV-Shows: Anzahl d. Beobachtungen")p <- df.reduced %>%
filter(category == "polit_tv")
ggplot(p, aes(year, wertung, color=p_group)) +
geom_point(size=p$count/1000) + geom_line() +
facet_wrap(~medium, ncol = 6) +
geom_hline(yintercept = 0, color="grey10",
size=0.3, linetype = 2) +
labs(x="", y="",
title="Politische TV-Shows (ungewichtet)",
substitle = "Pointsize: Obs/ 1000",
color="") +
theme(axis.text.x = element_text(angle = 90)) +
scale_x_continuous(breaks = seq(min(df.reduced$year),max(df.reduced$year),2)) require(ggiraph)
require(ggiraphExtra)radar <- df.reduced %>%
filter(category == "daily_print") %>%
group_by(medium, p_group) %>%
dplyr::summarise(wertung = mean(wertung, na.rm = T),
count = mean(count, na.rm = T)) %>%
ungroup() %>%
spread(key=p_group, value = wertung)
radar %>%
select(- count) %>%
ggRadar(aes(color=medium), rescale = F,
size=radar$count/10000,
alpha = 0, legend.position = "right") +
labs(title = "Tageszeitungen:\nWertung (ungewichtet) 1998-2012",
subtitle = "Pointsize = Obs / 10.000")
radar <- df.reduced %>%
filter(category == "magazine_print") %>%
group_by(medium, p_group) %>%
dplyr::summarise(wertung = mean(wertung, na.rm = T),
count = mean(count, na.rm = T)) %>%
ungroup() %>%
spread(key=p_group, value = wertung)
radar %>%
select(- count) %>%
ggRadar(aes(color=medium), rescale = F,
size=radar$count/1000,
alpha = 0, legend.position = "right") +
labs(title = "Magazine und Wochenzeitungen:\nWertung (ungewichtet) 1998 - 2012",
subtitle = "Pointsize = Obs / 1.000")
radar <- df.reduced %>%
filter(category == "news_tv") %>%
group_by(medium, p_group) %>%
dplyr::summarise(wertung = mean(wertung, na.rm = T),
count = mean(count, na.rm = T)) %>%
ungroup() %>%
spread(key=p_group, value = wertung)
radar %>%
select(- count) %>%
ggRadar(aes(color=medium), rescale = F,
size=radar$count/1000,
alpha = 0, legend.position = "right") +
labs(title = "Nachritensendungen: Wertung (ungewichtet)",
subtitle = "Pointsize = Obs / 1.000")
radar <- df.reduced %>%
filter(category == "polit_tv") %>%
group_by(medium, p_group) %>%
dplyr::summarise(wertung = mean(wertung, na.rm = T),
count = mean(count, na.rm = T)) %>%
ungroup() %>%
spread(key=p_group, value = wertung)
radar %>%
select(- count) %>%
ggRadar(aes(color=medium), rescale = F,
size=radar$count/500,
alpha = 0, legend.position = "right") +
labs(title = "Politische TV-Shows: Wertung (ungewichtet)",
subtitle = "Pointsize = Obs / 500")